Open Access
Enzo: An Adaptive Mesh Refinement Code for Astrophysics
Greg L. Bryan,Michael L. Norman,Brian W. O'Shea,Tom Abel,John H. Wise,Matthew J. Turk,Daniel R. Reynolds,David C. Collins,Peng Wang,Samuel W. Skillman,Britton D. Smith,Robert P. Harkness,James Bordner,Ji-hoon Kim,Michael Kuhlen,Hao Xu,Nathan J. Goldbaum,Cameron Hummels,Alexei G. Kritsuk,Elizabeth J. Tasker,Stephen Skory +20 more
TLDR
Enzo as discussed by the authors uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows, which can be run in one, two, and three dimensions, and supports a wide variety of physics, including hydrodynamics, ideal and non-ideal magnetohydrodynamic, N-body dynamics, primordial gas chemistry, optically thin radiative cooling of primordial and metal-enriched plasmas, and models for star formation and feedback in a cosmological context.Abstract:
This paper describes the open-source code Enzo, which uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows. The code is Cartesian, can be run in one, two, and three dimensions, and supports a wide variety of physics including hydrodynamics, ideal and non-ideal magnetohydrodynamics, N-body dynamics (and, more broadly, self-gravity of fluids and particles), primordial gas chemistry, optically thin radiative cooling of primordial and metal-enriched plasmas (as well as some optically-thick cooling models), radiation transport, cosmological expansion, and models for star formation and feedback in a cosmological context. In addition to explaining the algorithms implemented, we present solutions for a wide range of test problems, demonstrate the code's parallel performance, and discuss the Enzo collaboration's code development methodology.read more
Citations
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A new class of accurate, mesh-free hydrodynamic simulation methods
TL;DR: In this paper, a Lagrangian method for hydrodynamics is proposed to simultaneously capture advantages of both SPH and grid-based/adaptive mesh refinement (AMR) schemes.
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FIRE-2 simulations: physics versus numerics in galaxy formation
Philip F. Hopkins,Andrew Wetzel,Andrew Wetzel,Andrew Wetzel,Dušan Kereš,Claude André Faucher-Giguère,Eliot Quataert,Michael Boylan-Kolchin,Norman Murray,Christopher C. Hayward,Shea Garrison-Kimmel,Cameron Hummels,Robert Feldmann,Robert Feldmann,Paul Torrey,Xiangcheng Ma,Daniel Anglés-Alcázar,Kung-Yi Su,Matthew E. Orr,Denise Schmitz,Ivanna Escala,Robyn E. Sanderson,Michael Y. Grudić,Zachary Hafen,Ji-hoon Kim,Alex Fitts,James S. Bullock,Coral Wheeler,T. K. Chan,Oliver D. Elbert,Desika Narayanan +30 more
TL;DR: The Feedback In Realistic Environments (FIRE) project explores feedback in cosmological galaxy formation simulations as mentioned in this paper, which has been used to explore new physics (e.g. magnetic fields).
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Physical Models of Galaxy Formation in a Cosmological Framework
Rachel S. Somerville,Romeel Davé +1 more
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Similarity and Dimensional Methods in Mechanics
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MUFASA: Galaxy Formation Simulations With Meshless Hydrodynamics
TL;DR: The mufasa suite of cosmological hydrodynamic simulations as mentioned in this paper employs the gizmo meshless finite mass (MFM) code including H_2-based star formation, nine-element chemical evolution, two-phase kinetic outflows following scalings from the Feedback in Realistic Environments zoom simulations, and evolving halo mass-based quenching.
References
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